knitr::opts_knit$set(root.dir = normalizePath("."))

Loading needed libraries, check if you need to install packages

Read in phyloseq object and custom deseq functions

# Load phyloseq object as inc.physeq, not rarefied but unclassified OTUs removed if at phylum level
inc.physeq <- readRDS("data/RDS/not.rare.nounclass")

# LFC calculation function
who_diff_day <- function(DDS, choice1, choice2, phy.object){
  res = results(DDS, contrast = c("Treatment_Response", choice1, choice2), cooksCutoff = FALSE)
  #plotCounts(AlfalfaDDS, gene="OTU_311", intgroup="day")
  #Use above line to check if an OTU is increasing or decreasing depending on order of contrast
  alpha = 0.01
  #alpha = 0.1
  sigtab = res[which(res$padj < alpha), ]
  sigtab = cbind(as(sigtab, "data.frame"), as(tax_table(phy.object)[rownames(sigtab), ], "matrix"))
  theme_set(theme_bw())
  scale_fill_discrete <- function(palname = "Set1", ...) {
    scale_fill_brewer(palette = palname, ...)
  }
  # Phylum order
  x = tapply(sigtab$log2FoldChange, sigtab$Phylum, function(x) max(x))
  x = sort(x, TRUE)
  sigtab$Phylum = factor(as.character(sigtab$Phylum), levels=names(x))
  # Genus order
  x = tapply(sigtab$log2FoldChange, sigtab$Genus, function(x) max(x))
  x = sort(x, TRUE)
  sigtab$Genus = factor(as.character(sigtab$Genus), levels=names(x))
  #ggplot(sigtab, aes(x=Genus, y=log2FoldChange, color=phylum)) + geom_point(size=2) + 
  #  theme(axis.text.x = element_text(angle = -90, hjust = 0, vjust=1.0)) +
  #  ggtitle("Day 0 to Day 7")
  return(sigtab)
}

# function plot log2FoldChange 
log_plot <- function(sigtab,t1){
  sigtab <- sigtab %>%
    rownames_to_column(var = "OTU") %>%
    filter(log2FoldChange >= 2) 
  
  ggplot(sigtab, aes(x=Genus, y=log2FoldChange, color=Phylum)) + geom_point(size=2) + 
    coord_flip() +
    ggtitle(t1)
}

Alfalfa Responders

Early

## Early   
alf.early <- subset_samples(inc.physeq, Treatment_Response %in% c("Alfalfa_early", "Reference_early")) %>%
  filter_taxa(function(x) sum(x) >= 3, T) 

# Be very careful of the design formula in the who_diff_day() function
# This function also selects only LFC >= 2 and alpha 0.01 for significant and increasing otus to be returned
log.plot.early.alf <- alf.early %>%
  phyloseq_to_deseq2( ~ Treatment_Response) %>%
  DESeq(test = "Wald", fitType = "local") %>%
  who_diff_day("Alfalfa_early", "Reference_early", alf.early) %>%
  log_plot("Alfalfa OTUS in early group that are significantly changing compared to reference early")

# Save a data frame of these results
log.plot.early.alf.data <- log.plot.early.alf$data %>%
  mutate(trt = c("Alfalfa_early"))

# print plot with viridis color 
log.plot.early.alf + scale_colour_viridis_d(option = "plasma") +
  theme_dark()

Late

## Late 
alf.late <- subset_samples(inc.physeq, Treatment_Response %in% c("Alfalfa_late", "Reference_late")) %>%
  filter_taxa(function(x) sum(x) >= 3, T)

# Make deseq and plot as above
log.plot.late.alf <- alf.late %>%
  phyloseq_to_deseq2( ~ Treatment_Response) %>%
  DESeq(test = "Wald", fitType = "local") %>%
  who_diff_day("Alfalfa_late", "Reference_late", alf.late) %>%
  log_plot("Alfalfa OTUS in late group that are significantly changing compared to reference late")

# Save a data frame of these results
log.plot.late.alf.data <- log.plot.late.alf$data %>%
  mutate(trt = c("Alfalfa_late"))

# print plot with viridis color 
log.plot.late.alf + scale_colour_viridis_d(option = "plasma") +
  theme_dark()

# Common to both early and late with LFC >=2
otustokeep <- intersect(log.plot.early.alf.data$OTU, log.plot.late.alf.data$OTU)

# Trim and rename variables
early_alf_OTUS <- log.plot.early.alf.data %>%
  select(OTU, Phylum, Class, Order, Family, Genus, Alfalfa_early_log2FoldChange = log2FoldChange) 

late_alf_OTUS <- log.plot.late.alf.data %>%
  select(OTU, Phylum, Class, Order, Family, Genus, Alfalfa_late_log2FoldChange = log2FoldChange)

# join early and late
all_alf <- full_join(early_alf_OTUS, late_alf_OTUS)

Plot Alfalfa OTUs with LFC >= 2 in both early and late

This plot is showing the common OTUs with LFC > 3 while also showing the LFC of OTUs observed in only early or late, represented by the points landing below 2 on either axis. Common OTUs with LFC < 3 are left unlabeled.

p <- ggplot(all_alf,
       aes(x = Alfalfa_early_log2FoldChange, 
           y = Alfalfa_late_log2FoldChange,
           color = Phylum,
           label = OTU)) +
  geom_miss_point() +
  geom_text_repel(aes(label=ifelse(Alfalfa_early_log2FoldChange>3 & Alfalfa_late_log2FoldChange>3,as.character(OTU),'')),hjust=0,vjust=0) 

p + scale_colour_viridis_d(option = "plasma") +
  theme_dark()

# Save this list of alfalfa LFC > 2 for more plots
saveRDS(all_alf, file = "data/RDS/LFC_alf_OTUs_June19.RDS")

Plot a table of the Alfalfa OTUs with taxonomy

These OTUs had response greater than 3 in both early and late alfalfa

OTUs <- all_alf %>%
  filter(Alfalfa_early_log2FoldChange>3 & Alfalfa_late_log2FoldChange>3)

kable(OTUs) %>%
  kable_styling(bootstrap_options = "striped") %>%
  scroll_box(width = "100%", height = "400px")
OTU Phylum Class Order Family Genus Alfalfa_early_log2FoldChange Alfalfa_late_log2FoldChange
Otu00064 Proteobacteria Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas 5.426305 4.854536
Otu00098 Proteobacteria Deltaproteobacteria Myxococcales Nannocystaceae Nannocystis 3.656891 4.493757
Otu00138 Verrucomicrobia Verrucomicrobia_unclassified Verrucomicrobia_unclassified Verrucomicrobia_unclassified Verrucomicrobia_unclassified 4.040318 3.635486
Otu00149 Firmicutes Bacilli Bacillales Bacillaceae_1 Bacillus 3.235475 3.545502
Otu00151 Verrucomicrobia Verrucomicrobia_unclassified Verrucomicrobia_unclassified Verrucomicrobia_unclassified Verrucomicrobia_unclassified 4.155508 3.249719
Otu00222 Firmicutes Bacilli Bacillales Planococcaceae Sporosarcina 3.929644 3.827824
Otu00400 Bacteroidetes Bacteroidetes_incertae_sedis Ohtaekwangia Ohtaekwangia_unclassified Ohtaekwangia_unclassified 3.443471 4.371128
Otu00439 candidate_division_WPS-1 candidate_division_WPS-1_unclassified candidate_division_WPS-1_unclassified candidate_division_WPS-1_unclassified candidate_division_WPS-1_unclassified 3.679809 3.260877
Otu00494 Proteobacteria Gammaproteobacteria Pseudomonadales Pseudomonadaceae Pseudomonas 5.694554 3.973771
Otu00517 Proteobacteria Alphaproteobacteria Caulobacterales Caulobacteraceae Caulobacter 3.281417 3.061991
Otu00557 Firmicutes Bacilli Bacillales Planococcaceae Planococcaceae_unclassified 3.612917 3.111851
Otu00608 Planctomycetes Planctomycetia Planctomycetales Planctomycetaceae Planctomycetaceae_unclassified 3.306852 5.381203
Otu00614 Proteobacteria Gammaproteobacteria Enterobacteriales Enterobacteriaceae Enterobacteriaceae_unclassified 5.809232 4.037280
Otu00666 Proteobacteria Deltaproteobacteria Bdellovibrionales Bdellovibrionaceae Bdellovibrio 5.037616 4.181329
Otu00717 Verrucomicrobia Verrucomicrobiae Verrucomicrobiales Verrucomicrobiaceae Roseimicrobium 4.500848 3.479294
Otu00728 Proteobacteria Alphaproteobacteria Rhizobiales Rhizobiales_unclassified Rhizobiales_unclassified 4.802462 3.450962
Otu00737 Proteobacteria Deltaproteobacteria Myxococcales Myxococcales_unclassified Myxococcales_unclassified 3.494724 3.516254
Otu00808 Firmicutes Bacilli Bacillales Paenibacillaceae_1 Paenibacillus 4.413060 5.227285
Otu00832 Firmicutes Bacilli Bacillales Paenibacillaceae_1 Brevibacillus 5.091440 6.429205
Otu00847 Planctomycetes Planctomycetia Planctomycetales Planctomycetaceae Planctomycetaceae_unclassified 4.145200 4.795919
Otu00933 Proteobacteria Gammaproteobacteria Xanthomonadales Xanthomonadaceae Pseudoxanthomonas 4.604627 3.095884
Otu00953 Firmicutes Bacilli Bacillales Alicyclobacillaceae Tumebacillus 4.283473 4.255385
Otu00995 Actinobacteria Actinobacteria Actinomycetales Cellulomonadaceae Cellulomonas 4.665178 3.133432
Otu01203 Proteobacteria Deltaproteobacteria Myxococcales Polyangiaceae Byssovorax 4.122999 4.983632
Otu01264 Bacteroidetes Cytophagia Cytophagales Cytophagaceae Sporocytophaga 4.386096 3.703749
Otu01303 Proteobacteria Deltaproteobacteria Myxococcales Polyangiaceae Byssovorax 4.202493 3.879818
Otu01345 Verrucomicrobia Verrucomicrobiae Verrucomicrobiales Verrucomicrobiaceae Verrucomicrobium 4.859902 3.023443
Otu01355 Firmicutes Bacilli Bacillales Bacillales_unclassified Bacillales_unclassified 3.389340 4.358994
Otu01556 Proteobacteria Alphaproteobacteria Caulobacterales Caulobacteraceae Caulobacteraceae_unclassified 4.705944 3.320603
Otu01560 Verrucomicrobia Spartobacteria Spartobacteria_unclassified Spartobacteria_unclassified Spartobacteria_unclassified 3.580680 3.524340
Otu01602 Proteobacteria Gammaproteobacteria Xanthomonadales Xanthomonadaceae Pseudoxanthomonas 3.457083 3.412073
Otu01694 Proteobacteria Betaproteobacteria Burkholderiales Burkholderiaceae Cupriavidus 4.414078 3.667559
Otu01743 Firmicutes Bacilli Bacillales Alicyclobacillaceae Tumebacillus 3.816464 4.277178
Otu01749 Bacteroidetes Sphingobacteriia Sphingobacteriales Chitinophagaceae Chitinophagaceae_unclassified 3.527269 3.134364
Otu01800 Proteobacteria Alphaproteobacteria Alphaproteobacteria_unclassified Alphaproteobacteria_unclassified Alphaproteobacteria_unclassified 3.048795 3.782811
Otu02505 Proteobacteria Proteobacteria_unclassified Proteobacteria_unclassified Proteobacteria_unclassified Proteobacteria_unclassified 3.047140 3.041070

Compost Responders

Early

## Early   
comp.early <- subset_samples(inc.physeq, Treatment_Response %in% c("Compost_early", "Reference_early")) %>%
  filter_taxa(function(x) sum(x) >= 3, T) 

# Be very careful of the design formula in the who_diff_day() function
# This function also selects only LFC >= 2 and alpha 0.01 for significant and increasing otus to be returned
log.plot.early.comp <- comp.early %>%
  phyloseq_to_deseq2( ~ Treatment_Response) %>%
  DESeq(test = "Wald", fitType = "local") %>%
  who_diff_day("Compost_early", "Reference_early", comp.early) %>%
  log_plot("Compost OTUS in early group that are significantly changing compared to reference early")

# Save a data frame of these results
log.plot.early.comp.data <- log.plot.early.comp$data %>%
  mutate(trt = c("Compost_early"))

# print plot with viridis color 
log.plot.early.comp + scale_colour_viridis_d(option = "plasma") +
  theme_dark()

Late

## Late 
comp.late <- subset_samples(inc.physeq, Treatment_Response %in% c("Compost_late", "Reference_late")) %>%
  filter_taxa(function(x) sum(x) >= 3, T)

# Make deseq and plot as above
log.plot.late.comp <- comp.late %>%
  phyloseq_to_deseq2( ~ Treatment_Response) %>%
  DESeq(test = "Wald", fitType = "local") %>%
  who_diff_day("Compost_late", "Reference_late", comp.late) %>%
  log_plot("Compost OTUS in late group that are significantly changing compared to reference late")

# Save a data frame of these results
log.plot.late.comp.data <- log.plot.late.comp$data %>%
  mutate(trt = c("Compost_late"))

# print plot with viridis color 
log.plot.late.comp + scale_colour_viridis_d(option = "plasma") +
  theme_dark()

# Common to both early and late with LFC >=2
otustokeep <- intersect(log.plot.early.comp.data$OTU, log.plot.late.comp.data$OTU)

# Trim and rename variables
early_comp_OTUS <- log.plot.early.comp.data %>%
  select(OTU, Phylum, Class, Order, Family, Genus, Compost_early_log2FoldChange = log2FoldChange) 

late_comp_OTUS <- log.plot.late.comp.data %>%
  select(OTU, Phylum, Class, Order, Family, Genus, Compost_late_log2FoldChange = log2FoldChange)

# join early and late
all_comp <- full_join(early_comp_OTUS, late_comp_OTUS)

Plot Compost OTUs with LFC >= 2 in both early and late

This plot is showing the common OTUs with LFC > 3 while also showing the LFC of OTUs observed in only early or late, represented by the points landing below 2 on either axis. Common OTUs with LFC < 3 are left unlabeled.

p <- ggplot(all_comp,
       aes(x = Compost_early_log2FoldChange, 
           y = Compost_late_log2FoldChange,
           color = Phylum,
           label = OTU)) +
  geom_miss_point() +
  geom_text_repel(aes(label=ifelse(Compost_early_log2FoldChange>3 & Compost_late_log2FoldChange>3,as.character(OTU),'')),hjust=0,vjust=0) 

p + scale_colour_viridis_d(option = "plasma") +
  theme_dark()

# Save this list of compcompa LFC > 2 for more plots
saveRDS(all_comp, file = "data/RDS/LFC_comp_OTUs_June19.RDS")

Plot a table of the Compost OTUs with taxonomy

These OTUs had response greater than 3 in both early and late compcompa

OTUs <- all_comp %>%
  filter(Compost_early_log2FoldChange>3 & Compost_late_log2FoldChange>3)

kable(OTUs) %>%
  kable_styling(bootstrap_options = "striped") %>%
  scroll_box(width = "100%", height = "400px")
OTU Phylum Class Order Family Genus Compost_early_log2FoldChange Compost_late_log2FoldChange
Otu00022 Chloroflexi Thermomicrobia Sphaerobacterales Sphaerobacteraceae Sphaerobacter 7.333830 6.397724
Otu00092 Actinobacteria Actinobacteria Actinomycetales Glycomycetaceae Glycomyces 5.810926 3.448520
Otu00103 Proteobacteria Proteobacteria_unclassified Proteobacteria_unclassified Proteobacteria_unclassified Proteobacteria_unclassified 5.133128 6.224653
Otu00107 Proteobacteria Deltaproteobacteria Myxococcales Myxococcales_unclassified Myxococcales_unclassified 3.367819 5.149622
Otu00127 Proteobacteria Deltaproteobacteria Myxococcales Myxococcales_unclassified Myxococcales_unclassified 3.231907 3.339249
Otu00130 Actinobacteria Actinobacteria Actinomycetales Nocardiopsaceae Thermobifida 6.563901 5.247507
Otu00139 Proteobacteria Deltaproteobacteria Myxococcales Myxococcales_unclassified Myxococcales_unclassified 6.125951 5.054827
Otu00233 Proteobacteria Deltaproteobacteria Myxococcales Myxococcales_unclassified Myxococcales_unclassified 3.817501 4.428101
Otu00277 Proteobacteria Deltaproteobacteria Myxococcales Myxococcales_unclassified Myxococcales_unclassified 4.564746 4.587303
Otu00279 Actinobacteria Actinobacteria Actinomycetales Actinomycetales_unclassified Actinomycetales_unclassified 4.061483 3.124985
Otu00281 Proteobacteria Gammaproteobacteria Gammaproteobacteria_unclassified Gammaproteobacteria_unclassified Gammaproteobacteria_unclassified 4.718963 4.305848
Otu00298 Actinobacteria Actinobacteria Actinomycetales Thermomonosporaceae Actinomadura 3.960899 3.648603
Otu00331 Verrucomicrobia Opitutae Opitutales Opitutaceae Opitutaceae_unclassified 4.244084 4.339431
Otu00378 Chloroflexi Chloroflexi_unclassified Chloroflexi_unclassified Chloroflexi_unclassified Chloroflexi_unclassified 6.595953 5.560310
Otu00395 Proteobacteria Gammaproteobacteria Alteromonadales Alteromonadaceae Haliea 4.690868 4.920388
Otu00477 Proteobacteria Alphaproteobacteria Caulobacterales Caulobacteraceae Asticcacaulis 5.251184 3.067774
Otu00564 Planctomycetes Planctomycetia Planctomycetales Planctomycetaceae Pirellula 3.289989 3.060541
Otu00608 Planctomycetes Planctomycetia Planctomycetales Planctomycetaceae Planctomycetaceae_unclassified 3.623800 4.806582
Otu00655 Proteobacteria Deltaproteobacteria Myxococcales Myxococcales_unclassified Myxococcales_unclassified 6.766203 5.657540
Otu00737 Proteobacteria Deltaproteobacteria Myxococcales Myxococcales_unclassified Myxococcales_unclassified 5.019151 4.032267
Otu00847 Planctomycetes Planctomycetia Planctomycetales Planctomycetaceae Planctomycetaceae_unclassified 4.531744 4.556528
Otu00881 Proteobacteria Deltaproteobacteria Deltaproteobacteria_unclassified Deltaproteobacteria_unclassified Deltaproteobacteria_unclassified 3.045813 3.454454
Otu00952 Proteobacteria Gammaproteobacteria Gammaproteobacteria_unclassified Gammaproteobacteria_unclassified Gammaproteobacteria_unclassified 3.788132 4.282470
Otu00985 Chloroflexi Chloroflexi_unclassified Chloroflexi_unclassified Chloroflexi_unclassified Chloroflexi_unclassified 4.917675 3.056024
Otu01202 Planctomycetes Planctomycetia Planctomycetales Planctomycetaceae Planctomycetaceae_unclassified 3.086641 4.196262
Otu01212 Proteobacteria Alphaproteobacteria Alphaproteobacteria_unclassified Alphaproteobacteria_unclassified Alphaproteobacteria_unclassified 3.249781 5.466143
Otu01264 Bacteroidetes Cytophagia Cytophagales Cytophagaceae Sporocytophaga 4.666925 3.659067
Otu01298 Planctomycetes Planctomycetia Planctomycetales Planctomycetaceae Rhodopirellula 3.637536 5.278672
Otu01337 Bacteroidetes Bacteroidetes_incertae_sedis Ohtaekwangia Ohtaekwangia_unclassified Ohtaekwangia_unclassified 3.110281 3.514531
Otu01380 Firmicutes Bacilli Bacillales Paenibacillaceae_1 Paenibacillus 5.614766 3.242234
Otu01442 Proteobacteria Deltaproteobacteria Deltaproteobacteria_unclassified Deltaproteobacteria_unclassified Deltaproteobacteria_unclassified 3.829121 3.432062
Otu01488 Firmicutes Clostridia Halanaerobiales Halanaerobiaceae Halocella 3.450090 3.202642
Otu01490 Chloroflexi Chloroflexi_unclassified Chloroflexi_unclassified Chloroflexi_unclassified Chloroflexi_unclassified 4.851297 3.848434
Otu01874 Proteobacteria Proteobacteria_unclassified Proteobacteria_unclassified Proteobacteria_unclassified Proteobacteria_unclassified 3.347806 4.049496
Otu01912 Planctomycetes Planctomycetia Planctomycetales Planctomycetaceae Pirellula 3.337455 3.138712
Otu02494 Proteobacteria Alphaproteobacteria Sphingomonadales Sphingomonadaceae Sphingomonas 3.113915 3.611850

Mix Responders

Early

## Early   
mix.early <- subset_samples(inc.physeq, Treatment_Response %in% c("Mix_early", "Reference_early")) %>%
  filter_taxa(function(x) sum(x) >= 3, T) 

# Be very careful of the design formula in the who_diff_day() function
# This function also selects only LFC >= 2 and alpha 0.01 for significant and increasing otus to be returned
log.plot.early.mix <- mix.early %>%
  phyloseq_to_deseq2( ~ Treatment_Response) %>%
  DESeq(test = "Wald", fitType = "local") %>%
  who_diff_day("Mix_early", "Reference_early", mix.early) %>%
  log_plot("Mix OTUS in early group that are significantly changing mixared to reference early")

# Save a data frame of these results
log.plot.early.mix.data <- log.plot.early.mix$data %>%
  mutate(trt = c("Mix_early"))

# print plot with viridis color 
log.plot.early.mix + scale_colour_viridis_d(option = "plasma") +
  theme_dark()

Late

## Late 
mix.late <- subset_samples(inc.physeq, Treatment_Response %in% c("Mix_late", "Reference_late")) %>%
  filter_taxa(function(x) sum(x) >= 3, T)

# Make deseq and plot as above
log.plot.late.mix <- mix.late %>%
  phyloseq_to_deseq2( ~ Treatment_Response) %>%
  DESeq(test = "Wald", fitType = "local") %>%
  who_diff_day("Mix_late", "Reference_late", mix.late) %>%
  log_plot("Mix OTUS in late group that are significantly changing mixared to reference late")

# Save a data frame of these results
log.plot.late.mix.data <- log.plot.late.mix$data %>%
  mutate(trt = c("Mix_late"))

# print plot with viridis color 
log.plot.late.mix + scale_colour_viridis_d(option = "plasma") +
  theme_dark()

# Common to both early and late with LFC >=2
otustokeep <- intersect(log.plot.early.mix.data$OTU, log.plot.late.mix.data$OTU)

# Trim and rename variables
early_mix_OTUS <- log.plot.early.mix.data %>%
  select(OTU, Phylum, Class, Order, Family, Genus, Mix_early_log2FoldChange = log2FoldChange) 

late_mix_OTUS <- log.plot.late.mix.data %>%
  select(OTU, Phylum, Class, Order, Family, Genus, Mix_late_log2FoldChange = log2FoldChange)

# join early and late
all_mix <- full_join(early_mix_OTUS, late_mix_OTUS)

Plot Mix OTUs with LFC >= 2 in both early and late

This plot is showing the common OTUs with LFC > 3 while also showing the LFC of OTUs observed in only early or late, represented by the points landing below 2 on either axis. Common OTUs with LFC < 3 are left unlabeled.

p <- ggplot(all_mix,
       aes(x = Mix_early_log2FoldChange, 
           y = Mix_late_log2FoldChange,
           color = Phylum,
           label = OTU)) +
  geom_miss_point() +
  geom_text_repel(aes(label=ifelse(Mix_early_log2FoldChange>3 & Mix_late_log2FoldChange>3,as.character(OTU),'')),hjust=0,vjust=0) 

p + scale_colour_viridis_d(option = "plasma") +
  theme_dark()

# Save this list of mixmixa LFC > 2 for more plots
saveRDS(all_mix, file = "data/RDS/LFC_mix_OTUs_June19.RDS")

Plot a table of the Mix OTUs with taxonomy

These OTUs had response greater than 3 in both early and late mixmixa

OTUs <- all_mix %>%
  filter(Mix_early_log2FoldChange>3 & Mix_late_log2FoldChange>3)

kable(OTUs) %>%
  kable_styling(bootstrap_options = "striped") %>%
  scroll_box(width = "100%", height = "400px")
OTU Phylum Class Order Family Genus Mix_early_log2FoldChange Mix_late_log2FoldChange
Otu00022 Chloroflexi Thermomicrobia Sphaerobacterales Sphaerobacteraceae Sphaerobacter 5.603070 4.400343
Otu00098 Proteobacteria Deltaproteobacteria Myxococcales Nannocystaceae Nannocystis 3.368089 3.530743
Otu00103 Proteobacteria Proteobacteria_unclassified Proteobacteria_unclassified Proteobacteria_unclassified Proteobacteria_unclassified 4.425215 4.625760
Otu00130 Actinobacteria Actinobacteria Actinomycetales Nocardiopsaceae Thermobifida 4.795846 4.141254
Otu00139 Proteobacteria Deltaproteobacteria Myxococcales Myxococcales_unclassified Myxococcales_unclassified 5.804734 3.702383
Otu00222 Firmicutes Bacilli Bacillales Planococcaceae Sporosarcina 3.461706 3.132583
Otu00277 Proteobacteria Deltaproteobacteria Myxococcales Myxococcales_unclassified Myxococcales_unclassified 4.021133 3.214944
Otu00281 Proteobacteria Gammaproteobacteria Gammaproteobacteria_unclassified Gammaproteobacteria_unclassified Gammaproteobacteria_unclassified 3.755055 3.353680
Otu00298 Actinobacteria Actinobacteria Actinomycetales Thermomonosporaceae Actinomadura 3.171157 3.001881
Otu00331 Verrucomicrobia Opitutae Opitutales Opitutaceae Opitutaceae_unclassified 3.562399 3.430582
Otu00378 Chloroflexi Chloroflexi_unclassified Chloroflexi_unclassified Chloroflexi_unclassified Chloroflexi_unclassified 5.159133 3.273742
Otu00395 Proteobacteria Gammaproteobacteria Alteromonadales Alteromonadaceae Haliea 3.823497 3.638668
Otu00400 Bacteroidetes Bacteroidetes_incertae_sedis Ohtaekwangia Ohtaekwangia_unclassified Ohtaekwangia_unclassified 3.134202 3.736313
Otu00606 Bacteroidetes Bacteroidetes_incertae_sedis Ohtaekwangia Ohtaekwangia_unclassified Ohtaekwangia_unclassified 3.315817 3.283691
Otu00608 Planctomycetes Planctomycetia Planctomycetales Planctomycetaceae Planctomycetaceae_unclassified 3.575534 4.350690
Otu00737 Proteobacteria Deltaproteobacteria Myxococcales Myxococcales_unclassified Myxococcales_unclassified 4.105522 3.647305
Otu00808 Firmicutes Bacilli Bacillales Paenibacillaceae_1 Paenibacillus 4.657377 4.580972
Otu00847 Planctomycetes Planctomycetia Planctomycetales Planctomycetaceae Planctomycetaceae_unclassified 4.158366 4.386717
Otu00953 Firmicutes Bacilli Bacillales Alicyclobacillaceae Tumebacillus 3.136044 3.011227
Otu01202 Planctomycetes Planctomycetia Planctomycetales Planctomycetaceae Planctomycetaceae_unclassified 3.160087 3.758452
Otu01232 Proteobacteria Betaproteobacteria Betaproteobacteria_unclassified Betaproteobacteria_unclassified Betaproteobacteria_unclassified 3.035368 4.552961
Otu01264 Bacteroidetes Cytophagia Cytophagales Cytophagaceae Sporocytophaga 4.489835 3.262131
Otu01298 Planctomycetes Planctomycetia Planctomycetales Planctomycetaceae Rhodopirellula 3.816093 4.824337
Otu01939 Firmicutes Bacilli Bacillales Paenibacillaceae_1 Paenibacillus 3.779087 3.176198